Turn raw numbers into decisions. Go from zero to job-ready analytics in about five months — built around real datasets and portfolio-worthy reports.
Anyone can run a chart. The skill is explaining what it means. Every project below ends in a clear insight you could present to a manager.
Who it suits: You enjoy finding patterns in messy data and explaining what they mean to non-technical people.
Indicative 2026 starting ranges in India — actual pay varies widely by city, company, and skill. Salary is an outcome of skill and a strong project portfolio, not a guarantee.
The core toolkit: Python, stats, and SQL.
Variables, loops, functions, working with files.
DataFrames, cleaning, filtering, groupby.
Descriptive stats, distributions, probability.
SELECT, joins, aggregation, grouping.
Explore data and tell its story with charts.
Explore, clean, and handle missing data.
matplotlib and seaborn for clear charts.
Plotly, Power BI, or Tableau basics.
Turning findings into a clear narrative.
A full EDA writeup on a real dataset.
Test hypotheses and build predictive models.
A/B tests, p-values, significance.
Linear and logistic regression.
Decision trees and random forests.
K-means and customer segmentation.
Metrics, cross-validation, avoiding overfit.
Predict churn or price and evaluate it.
The workflow that makes you hireable.
Window functions, CTEs, subqueries.
Pivot tables, lookups, dashboards in Excel/Sheets.
Reproducible, version-controlled analysis.
Reports and decks for non-technical people.
A full case study from raw data to recommendation.
Projects beat certificates. Do them in order — each builds on the last. Put every one on GitHub with a clear README.
Pick any Kaggle dataset. Clean it, chart it, find 3 insights.
Sales, sports, or COVID data in Power BI / Tableau / Plotly.
Analyze an experiment and state whether the result is significant.
Predict churn or house prices; explain accuracy and drivers.
Raw data → analysis → model → written recommendation.
Click any resource to open it — free and well-known first, then build something with it.
Universal (any field): roadmap.sh · freeCodeCamp · GitHub Student Pack · Coursera
colab.research.google.com — free, browser-based, every library ready.
kaggle.com — thousands of free datasets and community notebooks.
Load a dataset, run .describe(), plot 3 charts. You've started.
PathAhead helps you choose the career that fits you — with guidance built for Intermediate students. Explore every roadmap in one place.
This roadmap is a free educational resource. Timelines are a guide — everyone learns at a different pace. Referenced resources (Kaggle Learn, freeCodeCamp, Khan Academy, Mode SQL Tutorial, StatQuest (YouTube)) are for learning only and are not affiliated with PathAhead.